amq-spec
>-
Perfil del activo
Investigación y trabajo de conocimiento
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Escenario
Agents de investigación
I need my agent to research a topic, compare sources, and produce a concise report.
Afinidad con Agent
Claude Code + OpenAI Agents + CLI
Funciona con Codex, Claude Code, Cursor, CLI o Agents personalizados.
Instalar
Listo
npx skills add avivsinai/agent-message-queue --skill amq-spec
Mantenimiento
Actual
1 días desde el último push
Riesgo
Requiere revisión
Dependency or permission surface needs review
Calidad de GitHub
82
65/100 Calidad · 63/100 Confianza
Etiquetas de cobertura
Notas de revisión
Dependency or permission surface needs review · Permission surface may require sandboxing
Tarjeta de adopción del Agent
Confianza, auditoría y preparación de instalación de un vistazo
Estas puntuaciones combinan metadatos públicos del repositorio, señales de revisión de OpenAgentSkill, actualidad de mantenimiento y preparación de instalación. Sirven para preseleccionar; no sustituyen la revisión humana.
Calidad
PrometedorUseful candidate, but compare it with alternatives before adopting.
Confianza
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Auditoría
Requiere revisiónRevisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.
Trust Score de OpenAgentSkill v5
Revisión humana antes de instalar
Choose a stronger alternative or inspect the source manually before any install attempt.
Estrellas
82 estrellas de GitHub
Actividad del repositorio
82 estrellas y 9 forks
Mantenimiento
1 días desde el último push
Licencia
MIT
Instalar
npx skills add avivsinai/agent-message-queue --skill amq-spec
Seguridad de instalación
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
secrets or environment access, shell or command execution
Resultados del Agent
Aún no hay datos de resultados del Agent
Documentación
Usable metadata, review docs
Resumen de riesgo
Revisar antes de producción
- Skill relies on external AMQ tool; not self-contained and requires prior installation, but this is clearly stated in pre-flight checks.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 82 GitHub stars
Preparación de instalación
Ruta de instalación disponible
- La ruta de instalación está disponible
- La evidencia del repositorio está disponible
- La licencia está declarada
- Aún no hay evidencia de resultados Agent-Proven
Metadatos legibles por Agent
Datos de decisión legibles por máquina para este skill.
Usa este bloque o el JSON integrado para decidir si un Agent debe instalar este skill, elegir una alternativa o pedir revisión humana primero.
Tareas adecuadas
- Flujos de Agents de investigación
- Equipos de Claude Code
- builders willing to evaluate younger projects
- Fuentes de búsqueda
Agents adecuados
Decisión de instalación
- Comando
- npx skills add avivsinai/agent-message-queue --skill amq-spec
- Política
- Bloquear
- Revisión humana
- Sí
Confianza y riesgo
- Confianza
- 55/100
- Auditoría
- 74/100
- Nivel de riesgo
- Requiere revisión
Ciclo de resultados
- Endpoint
- /api/agent/outcome
- ID del evento
- resolve
- Resultados
- 5
Comando de instalación
npx skills add avivsinai/agent-message-queue --skill amq-specNo usar cuando
- Equipos que necesitan un SLA con soporte del proveedor
- production agents without a repository review
- Skill relies on external AMQ tool; not self-contained and requires prior installation, but this is clearly stated in pre-flight checks.
- No OpenAgentSkill engagement data yet
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
Skill alternativo
Last30days Skill
53.5K Estrellas
npx skills add mvanhorn/last30days-skill -g
Skill alternativo
Academic Research Skills
38.4K Estrellas
npx skills add Imbad0202/academic-research-skills
Skill alternativo
GPT Researcher
28.0K Estrellas
npx skills add assafelovic/gpt-researcher
Skill alternativo
DeepResearch
19.8K Estrellas
npx skills add Alibaba-NLP/DeepResearch
Seguridad de Agent v2
34/100 · Evitar instalación automática
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
Alto
Ejecución de shell o comandos
Los metadatos del skill hacen referencia a terminal, CLI, shell, subprocesos o flujos de ejecución de comandos.
Medio
Acceso a red
El skill probablemente consulta páginas remotas, API, repositorios o servicios externos.
Medio
Acceso al sistema de archivos
El skill puede leer o escribir archivos de proyecto, documentos, artefactos generados o estado local.
Alto
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- Indicios de permisos de alto riesgo: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
Destinos de instalación
Instala este skill en tu flujo de Agent
Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install avivsinai-amq-specPlan de resolución de Agent
Deja que un Agent valide el ajuste antes de instalar.
La API Resolve devuelve la skill elegida, alternativas, política de seguridad, notas de auditoría, destino de instalación y un prompt listo para usar.
Abrir JSON
/api/agent/resolve?task=Use%20amq-spec%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Texto de Resolve
/api/agent/resolve?task=Use%20amq-spec%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Traspaso de instalación
/api/skills/avivsinai-amq-spec/install
Agent debe revisar
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copiar prompt
Task: Use amq-spec in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20amq-spec%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/avivsinai-amq-spec/install
Install command: npx skills add avivsinai/agent-message-queue --skill amq-spec
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Traspaso de Agent
Da al Agent la ruta de instalación, no otro directorio.
Usa el endpoint público para obtener el comando, la lista de seguridad, prompts y enlaces canónicos.
Traspaso de instalación
/api/skills/avivsinai-amq-spec/install
Formato de texto LLM
/api/skills/avivsinai-amq-spec/install?format=text
Buscar alternativas
/api/skills/search?q=amq-spec&limit=3
Prompt de Agent
Use amq-spec for this task. Review https://www.openagentskill.com/api/skills/avivsinai-amq-spec/install, then install with: npx skills add avivsinai/agent-message-queue --skill amq-specMetadatos del Registry
Perfil legible por Agent para seleccionar skills automáticamente.
La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.
Manifest
/api/registry/manifest/avivsinai-amq-spec
Texto LLM
/api/registry/manifest/avivsinai-amq-spec?format=text
Alias de instalación
/api/registry/install/avivsinai-amq-spec
Recomendar
/api/registry/recommend?task=Use%20amq-spec%20in%20an%20agent%20workflow&limit=3
Afinidad con Agent
Agents de investigación
Etiquetas de uso
Plataformas
Claude Code, OpenAI Agents
Informe de auditoría
Requiere revisión · 74/100
Revisión legible por máquina de la preparación de instalación, los metadatos de seguridad, el mantenimiento y el riesgo de adopción.
Panel de decisión de Agent
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Rol en la pila
Candidata de respaldo
Ajuste principal
Agents de investigación
Etiqueta de confianza
Prototipar primero
Ruta de instalación
Comando listo
Úsalo cuando
- Flujos de Agents de investigación
- Equipos de Claude Code
- builders willing to evaluate younger projects
Evidencia
- recent repository activity
- install command or GitHub repo available
- perfil de calidad 65/100
revisar primero
- Skill relies on external AMQ tool; not self-contained and requires prior installation, but this is clearly stated in pre-flight checks.
- No OpenAgentSkill engagement data yet
Ruta de implementación
- 1Instálalo en un Agent de sandbox y ejecuta una tarea de Agents de investigación de principio a fin.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Perfil de confianza
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Adopción en GitHub
Revisar82 estrellas de GitHub
Actividad de stars/forks
Revisar82 estrellas y 9 forks; la actividad de issues no está disponible en los metadatos actuales
Mantenimiento reciente
Aprobado1 días desde el último push
Claridad de licencia
AprobadoMIT
Señales positivas
- Revisión de IA aprobada
- La ruta de instalación está disponible
- La evidencia del repositorio está disponible
- Repositorio mantenido recientemente
- El comando de instalación no muestra un patrón de alto riesgo evidente
- El ciclo de resultados está listo, pero necesita la primera ejecución real de Agent
Revisar antes de instalar
- Skill relies on external AMQ tool; not self-contained and requires prior installation, but this is clearly stated in pre-flight checks.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 82 GitHub stars
- Stars/forks activity: 82 stars, 9 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Aún no hay informes reales de resultados del Agent
- Se requiere revisión humana antes de una instalación desatendida
Acción recomendada
Choose a stronger alternative or inspect the source manually before any install attempt.
Perfil de calidad
Prometedor candidato para flujos de Agent
Useful candidate, but compare it with alternatives before adopting.
Ajuste de flujo
Usa esta skill en estos escenarios
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Parse messy files
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Ajuste de flujo
Añadir a un flujo completo
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Lista de alternativas
Compara antes de instalar
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Resumen
--- name: amq-spec version: 0.66.0 # x-release-please-version description: >- Parallel-research-then-converge design workflow between two agents. Use this skill when the user wants two agents to independently think through a design problem before aligning on a solution — "spec X with codex", "design X together", "both agents think through X", "brainstorm architecture together", "parallel research then joint proposal", "think through separately then align", "careful thought from both sides before coding", or any variation where the user wants collaborative design rather than just splitting implementation work. Also use this when you receive a message labeled workflow:spec and need to know the correct receiver-side protocol. Not for sending simple messages or reviews (use /amq-cli), implementing completed designs, or creating document templates. argument-hint: "<description of what to design> [with <partner>]" metadata: short-description: Multi-agent collaborative spec workflow compatibility: claude-code, codex-cli ---
# /amq-spec — Collaborative Specification Workflow
This skill defines a structured two-agent specification flow.
Use canonical phases in order: `Research -> Discuss -> Draft -> Review -> Present -> Execute`
Detailed step-by-step protocol lives in `references/spec-workflow.md`. This file is the concise operational entrypoint.
## Parse Input
From the user prompt, extract: - **topic**: short kebab-case spec name (e.g., `auth-token-rotation`) - **partner**: partner agent handle (default: `codex`) - **problem**: the full design problem statement
If topic/problem are unclear, ask for clarification.
## Pre-flight
1. Verify AMQ is available: `which amq` 2. Verify the AMQ root is discoverable (`.amqrc`, AMQ env vars, or the default `.agent-mail` layout); otherwise run: `amq coop init` 3. Use thread name: `spec/<topic>`
## First Action: Send problem to partner IMMEDIATELY
The entire point of the spec workflow is parallel research — both agents exploring the problem independently, then comparing notes. Every second you spend researching before sending is a second your partner sits idle waiting for the problem statement. That's why the send comes first, even though your instinct might be to "research first to give better context."
```bash amq send --to <partner> --kind question \ --labels workflow:spec,phase:request \ --thread spec/<topic> --subject "Spec: <topic>" --body "<problem>" ```
Send the user's problem description verbatim — your own analysis goes in the research phase, not the kickoff. If you pre-analyze, you bias the partner's independent research, which defeats the purpose of having two perspectives.
## Label Convention
Labels are how both agents and the receiver-side protocol table know which phase the conversation is in. Use existing AMQ kinds plus labels to express spec workflow semantics:
| Phase | Kind | Labels | |---|---|---| | Problem statement | `question` | `workflow:spec,phase:request` | | Research findings | `brainstorm` | `workflow:spec,phase:research` | | Discussion | `brainstorm` | `workflow:spec,phase:discuss` | | Plan draft | `review_request` | `workflow:spec,phase:draft` | | Plan feedback | `review_response` | `workflow:spec,phase:review` | | Final decision | `decision` | `workflow:spec,phase:decision` | | Progress/ETA | `status` | `workflow:spec` |
## Quick Command Skeleton
```bash # Initiate spec with problem statement amq send --to <partner> --kind question \ --labels workflow:spec,phase:request \ --thread spec/<topic> --subject "Spec: <topic>" --body "<problem>"
# Submit independent research amq send --to <partner> --kind brainstorm \ --labels workflow:spec,phase:research \ --thread spec/<topic> --subject "Research: <topic>" --body "<findings>"
# Discuss and align amq send --to <partner> --kind brainstorm \ --labels workflow:spec,phase:discuss \ --thread spec/<topic> --subject "Discussion: <topic>" --body "<analysis>"
# Draft plan amq send --to <partner> --kind review_request \ --labels workflow:spec,phase:draft \ --thread spec/<topic> --subject "Plan: <topic>" --body "<plan>"
# Review plan amq send --to <partner> --kind review_response \ --labels workflow:spec,phase:review \ --thread spec/<topic> --subject "Review: <topic>" --body "<feedback>"
# Optional final decision message amq send --to <partner> --kind decision \ --labels workflow:spec,phase:decision \ --thread spec/<topic> --subject "Final: <topic>" --body "<final plan>" ```
## When You RECEIVE a Spec Message
If you receive a message labeled `workflow:spec`, your action depends on the phase:
| Label | Your action | |---|---| | `phase:request` | Read the problem statement, do your **own independent research first**, then submit findings as `brainstorm` + `phase:research` | | `phase:research` | **Before reading**: check if you've already submitted your own research on this thread. If not, do your own research and submit it first. This preserves research independence — reading the partner's findings before forming your own view contaminates your perspective. Once your research is submitted, read the thread and start discussion as `brainstorm` + `phase:discuss`. | | `phase:discuss` | Reply with your analysis, continue discussion until aligned | | `phase:draft` | Review the plan and send feedback as `review_response` + `phase:review`. Your job here is review, not implementation — the plan needs to survive scrutiny before anyone builds it. | | `phase:review` | Revise plan if needed, or confirm alignment | | `phase:decision` | Stop. A `phase:decision` message is agent-to-agent alignment, **not** user approval, so do **not** implement from a spec decision alone. Only the human authorizes implementation, recorded as a structural gate to the initialized human handle (conventionally `user`; see the Operator Gates section in /amq-cli). Wait until the initiator confirms the human approved on the gate thread and assigns you work. |
**Why the partner doesn't implement**: The spec workflow is a design process. The initiator owns the relationship with the user and presents the final plan. If the partner implements without approval, the user loses control over what gets built. The agent-to-agent `phase:decision` message is alignment, not authorization: human approval is a structural gate to the initialized human handle, and partner agents must not implement from a spec decision alone. Implementation starts only after the initiator explicitly tells you the human approved and assigns work.
## Protocol Discipline
These rules exist because violations silently break the workflow's value proposition:
- **Send before researching** — parallel research is the whole point. Pre-researching wastes your partner's time and biases the outcome toward your initial framing. - **Submit your own research before reading partner's** — reading first contaminates your independent perspective. Two agents who read the same code and reach the same conclusion is less valuable than two agents who explore independently and then compare notes. - **Don't skip phases** — each phase builds on the previous. Collapsing directly to a finished spec skips the discussion where misunderstandings surface. - **Use `spec/<topic>` threads and the label convention** — this is how both agents (and the tooling) know which phase the conversation is in. Without consistent labels, the receiver-side protocol table above breaks. - **Don't enter plan mode during research** if it blocks tool usage — you need tools to explore the codebase. - **Present the final plan to the user before executing, and raise a structural gate**. The initiator owns the user relationship. After the decision phase, present the plan in chat AND raise a structural human gate using the initialized human handle (conventionally `user`) on a stable `gate/<topic>` thread, then wait for explicit approval on that thread. The agent-to-agent `phase:decision` message is alignment only; partner agents must not implement from it. See the Operator Gates section in /amq-cli for canonical mechanics, seeding, and guardrails.
## Reference
For full protocol details, templates, and phase gates, see: - [references/spec-workflow.md](references/spec-workflow.md)
Detalles técnicos
- Versión
- 1.0.0
- Licencia
- MIT
- Última actualización
- 21 ago 2026
- Publicado
- 21 ago 2026
Resumen de decisión
Candidata de respaldo
recent repository activity
Auditoría
Revisión de instalación
Revisión de instalación y adopción
- Seguridad
- 73/100
- Mantenimiento
- 100/100
- Instalar
- 92/100
Evidencia probada por Agent
Evidencia probada por Agent
Informes de resultados tras resolver, revisar, instalar y una ejecución limitada.
- Tasa de éxito
- —
- Fallo reciente
- —
- Resultados
- 0
- Calidad de salida
- —
- Fallidos
- 0
- No relevante
- 0
- Instalaciones
- 0
- Bloqueado por riesgo
- 0
- Configuración necesaria
- 0
- Producción
- 0
Aún no hay datos de resultados de Agent. La primera ejecución puede informar éxito, configuración necesaria, bloqueos de riesgo, fallo o irrelevancia mediante /api/agent/outcome.
Instalar
Añadir al flujo de Agent
Gratis y de código abierto. Revisa el informe antes de instalar en Agents de producción.
Bucle de crecimiento
Kit para compartir
Borrador basado en un caso para amq-spec, listo para publicar manualmente en X.
Before you hand an agent source-backed research, give it a repeatable starting point. amq-spec: >- 82 stars https://www.openagentskill.com/skills/avivsinai-amq-spec?ref=x
Respuesta opcional con comando de instalación
Listing + install path for amq-spec: https://www.openagentskill.com/skills/avivsinai-amq-spec?ref=x Install: npx skills add avivsinai/agent-message-queue --skill amq-spec
Fuente de la ficha
Indexado por Registry
Esta ficha se indexó desde fuentes públicas y no está marcada como oficial hasta que se apruebe una reclamación de mantenedor.
- Creador
- avivsinai
- Indexado por
- Índice comunitario de OpenAgentSkill
La atribución enlaza al repositorio público o al perfil del creador. Los creadores pueden reclamar la ficha para actualizar las señales de propiedad.
Reclamar este skillReclamación del propietario
Reclamar esta ficha de skill
Esta ficha Indexado por Registry se atribuye a avivsinai, pero aún no está marcada como oficial. Reclámala para añadir una señal de propietario verificado y hacer más fiables futuras actualizaciones de lanzamiento, instalación y auditoría.
Kit de enlaces para creadores
Añade las insignias de evidencia a tu README
Muestra la ficha canónica, las señales actuales de confianza y auditoría, y evidencia real de Agent-Proven donde los desarrolladores evalúan el repositorio.
[](https://www.openagentskill.com/skills/avivsinai-amq-spec)
[](https://www.openagentskill.com/skills/avivsinai-amq-spec)
[](https://www.openagentskill.com/skills/avivsinai-amq-spec/audit)
[](https://www.openagentskill.com/skills/avivsinai-amq-spec)Autor
avivsinai
@avivsinai
Etiquetas
Afinidad con plataforma
Señales de salud
- Estrellas de GitHub
- 82
- Puntuación de calidad
- 36/100
- Último push de GitHub
- 21 ago 2026
- Pistas del framework
- Desconocido
- Vistas de OpenAgentSkill
- 0
- Copias de instalación
- 0
- Clics externos
- 0
Señal de comunidad
Comparte si este skill resulta útil para tu flujo de Agent. Los comentarios agregados mejoran la clasificación con el tiempo.
Confianza y seguridad
Do not auto-install
- Adopción en GitHub82 estrellas de GitHubRevisar
- Actividad de stars/forks82 estrellas y 9 forks; la actividad de issues no está disponible en los metadatos actualesRevisar
- Mantenimiento reciente1 días desde el último pushAprobado
- Claridad de licenciaMITAprobado
- Completitud de README/SKILL.mdLos metadatos públicos necesitan más contexto de README/SKILL.mdInfo
- Riesgo de dependencias/runtimecommand execution surface, credential or environment accessRevisar
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